ADOPTION TO REAL-TIME ONLINE LEARNING AMONG UNDERGRADUATES OF SRI LANKAN NATIONAL UNIVERSITIES: EXTENDING DECOMPOSED THEORY OF PLANNED BEHAVIOUR WITH IS SUCCESS MODEL

Abstract

Real-time online learning is a relatively new paradigm in education. As a result of the COVID-19 pandemic, the global education system has relied entirely on real-time teaching and learning. However, the adoption of a novel real-time online learning model has not been adequately addressed in literature. This study attempts to predict undergraduates' acceptance of real-time online learning at Sri Lankan national universities by extending the decomposed Theory of Planned Behavior (TPB) using the Information System Success Model (IS Success Model). The research employs PLS-SEM of Smart PLS 3 to determine the impact of the identified variables on the adoption of real-time online learning. The overall research design was deductive, positivist, and explanatory. A self-administered questionnaire was used to collect the data. Using an a priori sample size calculator, 127 was determined as the minimum sample size. Using the area-sampling technique, 382 responses were obtained. Decomposition of TPB indicated that the antecedents of attitude (ATT) were Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Perceived Risk (PR), and compatibility (COM). The antecedents of Perceived Behavioral Control (PBC) were Perceived Self-Efficacy (PSE) and Facilitating Conditions (FC). The proposed model has fourteen (14) hypotheses: The findings indicate a positive effect of PU (β= 0.391, p<0.05), PEOU (β= 0.227, p<0.05), and COM (β= 0.195, p<0.05) on Attitude with an R² value of 53.6%. However, PR did not influence attitudes. PSE (β= 0.438, p<0.05) and FC (β= 0.392, p<0.05) had positive effects on PBC, with an R² value of 59.2%. User Satisfaction was explained by System Quality (β= 0.209, p<0.05) and Information Quality (β= 0.564, p<0.05), with an R² value of 53.3%. Subjective Norm (β= 0.102, p<0.05), System Quality (β= 0.232, p<0.05), Information Quality (β= 0.238, p<0.05), and User Satisfaction (β= 0.249, p<0.05) positively affected Behavioral Intention to Use with an R² value of 56.2%, whereas Attitude and Perceived Behavioral Control did not. This study indicates that behavioral intentions to use real-time online learning will improve if the quality of the information and content made available improves.